Ground truth to top-1000; card regenerated

README.md

@@ -34,7 +34,8 @@ respectively), see [Encoding](#encoding).
 | `query_lens.npy` | int32 | `[50]` | true vectors per query, before padding |
 | `queries_ids.npy` | `<U2` | `[50]` | original query ids |
 | `qrels.test.tsv` | text | 66,336 rows | TREC qrels, `qid \t 0 \t docid \t relevance`, no header |
-| `gt_top100.tsv` | text | 5,000 rows | exact MaxSim top-100, see below |
+| `gt_top1000.tsv` | text | 50,000 rows | exact MaxSim top-1000, see below |
+| `gt_top100.tsv` | text | 5,000 rows | first 100 ranks of `gt_top1000.tsv`, same format |
 
 All positional indices (the `gt_top*.tsv` files, and the row order of every `.npy` file) refer to the
 order of `doc_ids.npy` and `queries_ids.npy`. Reordering either file invalidates the ground truth.
@@ -74,9 +75,9 @@ order of `doc_ids.npy` and `queries_ids.npy`. Reordering either file invalidates
 | query padding | rows at or beyond `query_lens[i]` in `queries.npy[i]` are exactly zero |
 | token_ids | tokenizer id of each kept document token (no skiplist, so every token), aligned 1:1 with `documents.npy` |
 
-## Ground truth: `gt_top100.tsv`
+## Ground truth: `gt_top1000.tsv` and `gt_top100.tsv`
 
-Exact brute-force MaxSim top-100 per query over the full corpus, from the vectors in this repo.
+Exact brute-force MaxSim top-1000 per query over the full corpus, from the vectors in this repo. `gt_top100.tsv` holds the first 100 ranks per query of the same lists (the original layout of these exports).
 
 No header; tab-separated `qidx  docidx  rank  score`:
 
@@ -89,12 +90,12 @@ No header; tab-separated `qidx  docidx  rank  score`:
 
 ## Retrieval quality
 
-Sanity check of the vectors, not a leaderboard number: `gt_top100.tsv` (exact MaxSim over the full
+Sanity check of the vectors, not a leaderboard number: `gt_top1000.tsv` (exact MaxSim over the full
 corpus) scored against `qrels.test.tsv` with ir_measures.
 
-| nDCG@10 | MRR@10 | Success@5 | Recall@100 | Recall@1000 | MAP@100 |
+| nDCG@10 | MRR@10 | Success@5 | Recall@100 | Recall@1000 | MAP@1000 |
 |---|---|---|---|---|---|
-| 0.8194 | 0.9467 | 1.0000 | 0.1570 | n/a (gt is top-100) | 0.1281 |
+| 0.8194 | 0.9467 | 1.0000 | 0.1570 | 0.5425 | 0.3181 |
 
 ## Loading
 
@@ -142,8 +143,12 @@ Checks run by the exporter on the files exactly as written here:
 - ✅ query vectors unit-norm — norm range [1.000000, 1.000000]
 - ✅ all vectors finite
 - ✅ gt_top100.tsv has k rows per query — 5000 rows, k=100
-- ✅ gt rows grouped by qidx with ranks 1..k and descending scores
-- ✅ gt indices in range
+- ✅ gt_top100.tsv rows grouped by qidx with ranks 1..k and descending scores
+- ✅ gt_top100.tsv indices in range
+- ✅ gt_top1000.tsv has k rows per query — 50000 rows, k=1000
+- ✅ gt_top1000.tsv rows grouped by qidx with ranks 1..k and descending scores
+- ✅ gt_top1000.tsv indices in range
+- ✅ gt_top100.tsv is the first 100 ranks of gt_top1000.tsv
 
 ## Provenance
 
@@ -151,4 +156,4 @@ Checks run by the exporter on the files exactly as written here:
 |---|---|
 | exported | 2026-09-25 |
 | hardware | Tesla V100S-PCIE-32GB |
-| revised | 2026-09-28: card regenerated; every other file unchanged |
+| revised | 2026-09-29: ground truth extended to top-1000 (`gt_top1000.tsv`, exact MaxSim over this repo's vectors on Tesla V100S-PCIE-32GB); `gt_top100.tsv` rewritten as its first 100 ranks: 11 rows differ from the previous file, 10 with a different document at that rank, scores moving by at most 0.000002 |

gt_top100.tsv

@@ -230,8 +230,8 @@
 2	98245	30	15.809555
 2	69655	31	15.808745
 2	102335	32	15.805311
-2	137315	33	15.804846
-2	96038	34	15.804846
+2	96038	33	15.804846
+2	137315	34	15.804846
 2	168236	35	15.804804
 2	92985	36	15.803965
 2	150466	37	15.803871
@@ -1176,8 +1176,8 @@
 11	86345	76	14.319447
 11	109158	77	14.319123
 11	92672	78	14.318392
-11	161959	79	14.318081
-11	27627	80	14.318081
+11	27627	79	14.318081
+11	161959	80	14.318081
 11	58018	81	14.317915
 11	102054	82	14.317609
 11	166459	83	14.317333
@@ -2074,8 +2074,8 @@
 20	1148	74	11.526816
 20	67979	75	11.526806
 20	151011	76	11.526300
-20	167010	77	11.525697
-20	70307	78	11.525697
+20	70307	77	11.525697
+20	167010	78	11.525697
 20	105804	79	11.525696
 20	89035	80	11.524739
 20	89036	81	11.524689
@@ -4232,8 +4232,8 @@
 42	124155	32	17.450447
 42	106033	33	17.449821
 42	113589	34	17.448311
-42	155031	35	17.446857
-42	67262	36	17.446857
+42	67262	35	17.446857
+42	155031	36	17.446857
 42	109425	37	17.446609
 42	34847	38	17.445608
 42	158736	39	17.442848
@@ -4796,7 +4796,7 @@
 47	112360	96	21.243443
 47	101681	97	21.243160
 47	30867	98	21.243145
-47	170999	99	21.237846
+47	170999	99	21.237844
 47	26682	100	21.237015
 48	73595	1	27.100231
 48	73632	2	27.011673
@@ -4873,8 +4873,8 @@
 48	92630	73	26.842239
 48	130457	74	26.842043
 48	99805	75	26.841499
-48	95575	76	26.840677
-48	44526	77	26.840677
+48	44526	76	26.840677
+48	95575	77	26.840677
 48	73367	78	26.840328
 48	61032	79	26.839924
 48	36687	80	26.839666